Christian Schüldt

A Low-Complexity Delayless Selective Subband Adaptive Filtering Algorithm

Adaptive filters of significant order, requiring high computational complexity, are necessary in many applications such as acoustic echo cancellation and wideband active noise control. Successful approaches to lessen the computational complexity of such filters are subband methods, and partial updating schemes where only a part of the filter is updated at each instant. To avoid the time delay introduced by the subband-splitting, delayless structures which reconstructs a fullband filter, producing delayless output, from the adaptive subband filters have been proposed. This paper proposes a delayless subband adaptive filter partial updating scheme, where the general idea is to only update the most misadjusted subband filter(s). Analysis in terms of mean square deviation is presented and shows that the fullband filter convergence speed is significantly increased, even for flat spectrum signals, as compared to traditional periodic subband filter update with the same computational complexity. Echo cancellation simulations with an artificial system to verify the analysis, using both flat spectrum signals and speech, is also presented, as well as offline calculations using signals from a real system.

Adaptive filter length selection for acoustic echo cancellation

The number of coefficients in an adaptive finite impulse response filter-based acoustic echo cancellation setup is an important parameter, affecting the overall performance of the echo cancellation. Too few coefficients give undermodelling and too many cause slow convergence and an additional echo due to the mismatch of the extra coefficients. This paper proposes a method to adaptively determine the filter length, based on estimation of the mean square deviation. The method is primarily intended for identifying long non-sparse systems, such as a typical impulse response from an acoustic setup. Simulations with band limited flat spectrum signals are used for verification, showing the behavior and benefits of the proposed algorithm. Furthermore, off-line calculation using recorded speech signals show the behavior in real situations and comparison with another state-of-the-art variable filter length algorithm shows the advantages of the proposed method.

A Delay-Based Double-Talk Detector

When an adaptive filter is used for echo cancellation, it is essential to prevent the filter from diverging in situations when the echo signal is contaminated with near-end disturbance, i.e., during double-talk. This paper presents an extension of a previously proposed double-talk detector for improved performance. It is shown that the computational complexity of the proposed detector is lower than that of the well-used normalized cross correlation (NCC) double-talk detector, at the cost of performance. Further, it is shown that there can be a significant performance difference, in terms of detecting double-talk, between having a fixed echo cancellation filter, which is a common strategy in objective evaluation techniques, and an adaptive filter, which is more close to realistic conditions.

Efficient multichannel NLMS implementation for acoustic echo cancellation

An acoustic echo cancellation structure with a single loudspeaker and multiple microphones is, from a system identification perspective, generally modelled as a single-input multiple-output system. Such a system thus implies specific echo-path models (adaptive filter) for every loudspeaker to microphone path. Due to the often large dimensionality of the filters, which is required to model rooms with standard reverberation time, the adaptation process can be computationally demanding. This paper presents a selective updating normalized least mean square (NLMS)-based method which reduces complexity to nearly half in practical situations, while showing superior convergence speed performance as compared to conventional complexity reduction schemes. Moreover, the method concentrates the filter adaptation to the filter which is most misadjusted, which is a typically desired feature.

Low-Complexity Network Echo Cancellation Approach for Systems Equipped With External Memory

Long delays and sparseness characterize impulse responses in telecommunication networks and a vast number of solutions for network echo cancellation have been proposed over the years. In this paper, an approach for detecting dispersive regions of a sparse impulse response and a proportionate normalized least mean square (PNLMS)-based selective updating approach are combined with an adaptive double-talk detector to form a complete solution for echo cancellation. The proposed solution has low computational complexity and is targeted for systems equipped with external memory.

An improved deviation measure for two-path echo cancellation

Parallel adaptive filters have been proposed for echo cancellation to solve the dead-lock problem, occurring when the echo is detected as near-end speech after a severe echo-path change; causing the updating of the adaptive filter to halt. To control the parallel filters and monitor their performance, estimates of the filter deviation (i.e. the squared norm of the filter mismatch vector) are typically used. This paper presents a modification of a filter mismatch estimator. The proposed modification requires slightly more computational resources than the original measure, but provides a significant improvement in terms of robustness during double-talk. This is shown both analytically and through simulations.

A hybrid acoustic echo canceller and suppressor

Wideband communication is becoming a desired feature in telephone conferencing systems. This paper proposes a computationally efficient echo suppression control algorithm to be used when increasing the bandwidth of an audio conferencing system, e.g. a conference telephone. The method presented in this paper gives a quality improvement, in the form of increased bandwidth, at a negligible extra computational cost. The increase in bandwidth is obtained through combining a conventional acoustic echo cancellation unit and an acoustic echo suppression unit, i.e. a hybrid echo canceller and suppressor. The proposed solution was implemented in a real-time system. Frequency analysis combined with subjective tests showed that the proposed method extends the bandwidth, while maintaining high quality.

Low-Complexity Adaptive Filtering Implementation for Acoustic Echo Cancellation

Acoustic echo cancellation is generally achieved with adaptive FIR filters. Due to the often large dimensionality of the adaptive filters, required to model rooms with standard reverberation time, the adaptation process can be computationally demanding. This paper presents a block based selective updating method which reduces the complexity with nearly a half in practical situations, while showing superior convergence speed performance as compared to conventional partial update complexity reduction schemes

Robust low-complexity transfer logic for two-path echo cancellation

A well used approach for echo cancellation is the two-path method, where two adaptive filters in parallel are utilized. Typically, one filter is continuously updated, and when this filter is considered better adjusted to the echo-path than the other filter, the coefficients of the better adjusted filter is transferred to the other filter. When this transfer should occur is controlled by the transfer logic. This paper proposes transfer logic that is both more robust and more simple to tune, owing to fewer parameters, than the conventional approach. Extensive simulations show the advantages of the proposed method.

An improved adaptive gain equalizer for noise reduction with low speech distortion

In high-quality conferencing systems, it is desired to perform noise reduction with as limited speech distortion as possible. Previous work, based on time varying amplification controlled by signal-to-noise ratio estimation in different frequency subbands, has shown promising results in this regard but can suffer from problems in situations with intense continuous speech. Further, the amount of noise reduction cannot exceed a certain level in order to avoid artifacts. This paper establishes the problems and proposes several improvements. The improved algorithm is evaluated with several different noise characteristics, and the results show that the algorithm provides even less speech distortion, better performance in a multi-speaker environment and improved noise suppression when speech is absent compared with previous work.